Rankiteo Logo
Rankiteo
Leader in Cyber Underwriting
Loading...
NEWRankiteo Cyber Underwriting Desktop - Score, price, and bind from your desktop
WindowsmacOSLinux
Download
Analyze » Eliza » ELI1764872418

Incident Score: Analysis & Impact (ELI1764872418)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-64
Company Score Before Incident750 / 1000
Company Score After Incident686 / 1000
Company LinkView Eliza Profile
INCIDENT NUMBERELI1764872418
Type of Cyber IncidentBreach
ATTACK VECTORUnauthorized system access
DATA EXPOSEDLimited customer identifiable information and...
INCIDENT DATE03/12/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of Eliza's Breach and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts Eliza Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the Eliza breach identified under incident ID ELI1764872418.

The analysis begins with a detailed overview of Eliza's information like the linkedin page: https://www.linkedin.com/company/elizahq, the number of followers: 561, the industry type: Software Development and the number of employees: 11 employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 750 and after the incident was 686 with a difference of -64 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on Eliza and their customers.

On 09 November 2025, OpenAI disclosed Third-Party Data Breach issues under the banner "OpenAI Third-Party Breach via Mixpanel".

OpenAI was impacted by a third-party breach affecting analytics company Mixpanel, exposing limited user data.

The disruption is felt across the environment, affecting Mixpanel's systems, and exposing Limited customer identifiable information and analytics information.

In response, and stakeholders are being briefed through Data breach incident notification on website.

The case underscores how with advisories going out to stakeholders covering Notification on OpenAI's website regarding the breach.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

MITRE ATT&CK® Correlation Analysis

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Trusted Relationship (T1199) with high confidence (90%), with evidence including third-party breach affecting analytics company Mixpanel, and openAI leverages Mixpanel’s data analytics services. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating attacker exported a dataset containing limited customer identifiable information and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating attacker gained unauthorized access to part of their systems and exported a dataset. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with moderate confidence (60%), supported by evidence indicating mixpanel’s systems accessed; OpenAI uses Mixpanel for API user activity tracking. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating dataset containing limited customer identifiable information and analytics information. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Sources & References